Search Method and System

ABSTRACT

The present disclosure discloses a search method and system. A method obtains a first search result set of first search results relevant to query data submitted by a client. According to a first relevance score and a preset diversity field of each first search result in the first search result set, a second relevance score of each first search result is calculated. The preset diversity field represents an attribute category of a respective first search result. According to the first relevance score and the second relevance score, a relevance parameter score for each first search result is generated. According to a preset number of second search results and the relevance parameter score, the present number of second search results are extracted from the first search result set to display to the client. The technique achieves lower consumption of system resources, faster computation speed and more flexibility in diversification of search results.

CROSS REFERENCE TO RELATED PATENT APPLICATIONS

This application is a national stage application of an internationalpatent application PCT/US10/51332, filed Oct. 4, 2010, which claimspriority from Chinese Patent Application No. 200910211788.X filed onNov. 12, 2009, entitled “SEARCH METHOD AND SYSTEM,” which applicationsare hereby incorporated in their entirety by reference.

TECHNICAL FIELD

The present disclosure relates to the network data processing field, andmore particularly relates to a search method and system.

BACKGROUND

In a search process by a search engine, search results may be secondlyranked according to some attributes (such as geography, source, orsubject) so that the top n (n>=1) search results present diversity ofdistribution in terms of those attributes. This is referred to asdiversification of search results. In the context of e-commerce search,search results are often ranked according to relevance or time. Thus asupplier would continuously publish information of a given product sothis product can occupy top pages of the search results, therebymaliciously depriving the product display opportunity of one or moreother suppliers and causing certain troubles to general users who may beattempting to find other products.

To avoid such problem, the current technologies provide a search methodto extract and categorize search results based on relevance. Thedetailed implementation process is as follows: search results arepre-categorized based on relevance, search results with similarrelevance scores are classified into a same category, and search resultsfrom each category are then extracted. The extraction includes:selecting a field as a basis for diversity, such as uid (a uniqueidentification of supplier) for example. Then the search results wouldinclude the products from a diversity of suppliers. In practice, thesearch results are classified into many sub-sets according to uid score.The search results for the same uid are classified into a same sub-set,and are ranked according to their relevance scores from high to low inthe same sub-set. The m (m>=1) most relevant search results in eachsub-set are extracted and displayed at top several pages of the searchresults. Therefore, the search results in the top several pages caninclude products from different uids, or suppliers.

The above-described process based on the current technologies requiresthe classification of sub-sets and ranking according to uid. Althoughsuch process can implement diversification of search results to acertain extent, the current technologies need to re-organize all of thesearch results in the extraction and classification process. Thisrequires copying of the search results in the system memory and thusconsumes a large volume of resources at the search engine server, suchas time and expenditure of hardware systems. This would cause lowperformance of the search engine. Further, the ranking in each sub-setis in fact not completely necessary. Thus the current technologies alsoconduct some calculations that may be unnecessary and waste the systemresources for such calculation. In addition, although the currenttechnologies use the classification based on relevance to balance thediversity and relevance of the search results to a certain extent, thecurrent technologies cannot use a fixed classification interval tocorrectly classify all search results. As shown in the FIG. 1, aninterval classification may be proper for a query A, and may be improperfor a query B. It shows that the search results with similarrelativities are classified into the same interval for the query A.However, the search results with similar relevance are not regularlyclassified into the same interval for the query B. Thus the currenttechnologies lack flexibility.

In general, a pending challenge before one of ordinary person in theprior art is to creatively submit a search method to resolve the problemof over-consuming server resources under the current technologies.

SUMMARY OF THE DISCLOSURE

The present disclosure provides a search method to resolve the problemof low performance of search engine server arising from over-consumptionof server resources under the current technologies. Further, the searchmethod can also improve flexibility in searching.

The present disclosure also provides a search system to ensure theimplementation and application of the above method.

In one aspect, a search method may comprise: according to query datasubmitted by a client, obtaining a first search result set of firstsearch results relevant to the query data; according to a firstrelevance score and a preset diversity field of each first search resultin the first search result set, calculating a second relevance score ofeach first search result, the preset diversity field representing anattribute category of a respective first search result; according to thefirst relevance score and the second relevance score, generating arelevance parameter score for each first search result; and according toa preset number of second search results and the relevance parameterscore, extracting the present number of second search results from thefirst search result set to display to the client. In one embodiment,calculating the second relevance score of each first search result maycomprise: according to the preset diversity field of each first searchresult in the first search result set, classifying the first searchresult set to obtain a respective subset corresponding to eachrespective attribute category of the first search result set; accordingto the first relevance score in each subset, obtaining a correspondingranking position of a respective first search result; and according to apreset relationship between the ranking position of the respective firstsearch result and the second relevance score, obtaining the secondrelevance score of each first search result.

In one embodiment, extracting the preset number of second search resultsfrom the first search result set to display to the client may comprise:according to the relevance parameter score, ranking each subset afterclassification of the first search results; and according to a rankingorder, extracting the preset number of second search resultsrespectively from the ranked subsets, the preset number of second searchresults being a product of a number of diversity values and a number ofrecurring extractions.

In one embodiment, the method may further comprise: storing the querydata, the preset number of second search results, and a correspondingrelationship between the query data and the preset number of secondsearch results into a database.

In one embodiment, obtaining the first search result set of first searchresults relevant to the query data may comprise: according to the firstrelevance score, conducting a search based on the query data submittedby the client; and according to the preset diversity field, extractingthe first search results from search results of the search.

In one embodiment, the method may further comprise: displaying thepreset number of second search results to the client.

In one embodiment, generating the relevance parameter score of eachfirst search result may comprise: summing the first relevance score andthe second relevance score to provide the relevance parameter score foreach first search result.

In another aspect, a search system may comprise: a retrieval unit that,according to query data submitted by a client, obtains a first searchresult set of first search results relevant to the query data; acalculation unit that, according to a first relevance score and a presetdiversity field of each first search result in the first search resultset, calculates a second relevance score of each first search result,the preset diversity field representing an attribute category of arespective first search result; a configuration unit that, according tothe first relevance score and the second relevance score, generates arelevance parameter score of each first search result; and an extractionunit that, according to a preset number of second search results and therelevance parameter score, extracts the present number of second searchresults from the first search result set to display to the client.

In one embodiment, the calculation unit may comprise: a first retrievalsub-unit that, according to the preset diversity field, classifies thefirst search result set to obtain a respective subset corresponding toeach respective attribute category of the first search result set; asecond retrieval sub-unit that, according to the first relevance scorein each subset, obtains a corresponding ranking position of a respectivefirst search result; and a matching unit that, according to a presetrelationship between the ranking position of each first search resultand the second relevance score, obtains the second relevance score ofthe respective first search result.

In one embodiment, the extraction unit may comprise: a ranking sub-unitthat, according to the relevance parameter score, ranks each firstsearch result; and a first extraction sub-unit that, according to aranking order, extracts the preset number of second search results fromthe ranked subsets, the preset number of second search results being aproduct of a number of diversity values and a number of recurringextractions.

In one embodiment, the system may further comprise: a store unit thatstores the query data, the preset number of second search results, and acorresponding relationship between the query data and the preset numberof second search results into a database.

In one embodiment, the retrieval unit may comprise: a searching sub-unitthat, according to the first relevance score, conducts a search based onthe query data submitted by the client; and a second extraction sub-unitthat, according to the preset diversity field, extracts first searchresults from search results of the search.

In one embodiment, the system may further comprise: a display unit thatdisplays the preset number of second search results to the client.

In one embodiment, the configuration unit may sum the first relevancescore and the second relevance score to provide the relevance parameterscore of each first search result.

Compared with the current technologies, the present disclosure hasfollowing advantages:

The present disclosure uses an addition of the first relevance scoreunder the current technologies and the calculated second relevance scoreas the relevance parameter. The present disclosure uses the relevanceparameter to conduct a second extraction of the search results so thatthe search results are more diversified. Further, the present disclosurealso conducts optimization in the diversification process to ensure lessconsumption of system resources, faster calculation, and moreflexibility, thereby improving performance of the search engine server.It is appreciated that not every embodiment of the present disclosureneeds to achieve all of the above advantages.

DESCRIPTION OF DRAWINGS

To better illustrate embodiments of the present disclosure or techniquesof the current technologies, the following is a brief introduction ofFigures to be used in descriptions of the embodiments. The followingFigures only relate to some embodiments of the present disclosure. Aperson of ordinary skill in the art can obtain other figures accordingto the Figures in the present disclosure without creative efforts.

FIG. 1 illustrates an interface diagram of classification in the currenttechnologies.

FIG. 2 illustrates an exemplary flowchart of a first embodiment of asearch method in accordance with the present disclosure.

FIG. 3 illustrates an exemplary flowchart of a second embodiment of asearch method in accordance with the present disclosure.

FIG. 4 illustrates an exemplary flowchart of a third embodiment of asearch method in accordance with the present disclosure.

FIG. 5 illustrates an exemplary diagram of a first embodiment of asearch system in accordance with the present disclosure.

FIG. 6 illustrates an exemplary diagram of a second embodiment of asearch system in accordance with the present disclosure.

FIG. 7 illustrates an exemplary diagram of a third embodiment of asearch system in accordance with the present disclosure.

DETAILED DESCRIPTION

The present disclosure, by reference to the Figures in the drawings,clearly and fully describes techniques in embodiments. The Figures onlyrelate to some embodiments instead of all embodiments of the presentdisclosure. A person of ordinary skill in the art can obtain otherembodiment according to the embodiments in the present disclosurewithout creative efforts. All such embodiments belong to a protectionscope of the present disclosure.

The present disclosure may be used in an environment or in aconfiguration of universal or specialized computer systems. Examplesinclude a personal computer, a server computer, a handheld device or aportable device, a tablet device, a multi-processor system, and adistributed computing environment including any system or device above.

The present disclosure may be described within a general context ofcomputer-executable instructions executed by a computer, such as aprogram module. Generally, a program module includes routines, programs,objects, modules, and data structure, etc., for executing specific tasksor implementing specific abstract data types. The present disclosure mayalso be implemented in a distributed computing environment. In thedistributed computing environment, a task may be executed by remoteprocessing devices which are connected through a communication network.In distributed computing environment, the program module may be locatedin one or more storage media (which include storage devices) of one ormore local and/or remote computers.

One of the main ideas of the present disclosure may be summarized below.The current technologies, according to query data submitted by a client,may be used to obtain a first search result set that is relevant to thequery data. According to a first relevance score and a preset diversityfield of each first search result in the first search result set, asecond relevance score of each first search result is calculated. Thepreset diversity field represents an attribute category of a respectivefirst search result, which is a key step in this inventive concept.According to the first relevance score and the second relevance score, arelevance score of each first search result is generated. Finally,according to a preset number of one or more second search results andthe relevance score, the one or more second search results are extractedfrom the first search result set to be displayed to the client.

Such extracted second search results can show diversification of thesearch results, and avoid consumption of a lot of resources at thesearch engine server, such as time and expenditure of hardware systems,thereby improving performance of the search engine server. Further,methods of the present disclosure can also be adapted for distributionof more search result sets, thereby increasing flexibility.

FIG. 2 illustrates an exemplary method of a first embodiment inaccordance with the present disclosure. The method is described below.

At 201, according to query data submitted by a client, the methodobtains a first search result set relevant to the query data.

In the technology field related to search engines, a user's query isusually represented as symbol query, or Query, with a result matchingthe Query represented as Doc, and a result set matching the Query is aDoc set represented as {Doc}.

In this step, after the client submits the Query, a first step of aninternal processing procedure of the search engine server may be to mapthe Query onto the {Doc}, e.g., Query→{Doc}, wherein the symbol “→”represents mapping. At the meantime, the search engine server calculatesthe first relevance score (Score 1) for each Doc in the {Doc}. The Score1 is used to represent the extent of matching between a current Doc anda current Query, e.g., {Doc}→{Doc, Score 1} in a form of symbols. Themapping process is a process that matches search results based on theQuery. Any algorithms for relevance can be used to calculate Score 1,such as classical term frequency-inverse document frequency (TF-IDF)algorithm. Some other methods can also be used, such as information gain(IG), mutual information (MI), and entropy.

It is noted that the search engine server can define any algorithm toobtain the first search result. The present disclosure does not limitthe search engine server to choose a specific algorithm to obtain thefirst search result set. Thus, if the algorithm for relevance isdifferent in this step, the first search result obtained afterwards mayalso be different. This will not influence subsequent steps of themethod because the present disclosure targets diversification of thefirst search result and needs not to restrict the method to obtain thefirst search result.

At 202, according to a first relevance score and a preset diversityfield of each first search result in the first search result set, themethod calculates a second relevance score of each first search result,the preset diversity field representing an attribute category of arespective first search result.

After calculation of the Score 1 of each first search result in thefirst search result set, a second relative score (Score 2) is calculatedbased on the preset diversity field and the Score 1. The presetdiversity field represents the attribute category of the respectivefirst search result, such as a uid (an identification of supplier) ofeach search result or geographical location information in e-commercevertical search, for example. The Score 2 is used to represent a scorebased on the Score 1 and ranking of each first search result under thediversity field. In practical applications, a preset function can beused for the Score 2, and parameters for the preset function are set upas the Score 1 and the ranking position of each first search result. Areturn value of the function is a value of the Score 2. The setupranking position in the function has certain association with the Score2. For example, the higher ranking of the first search result, thehigher the value of Score 2 is. Based on different situations, one ofordinary skill in the art would be able to use other associate methodsbetween the ranking position and the Score 2.

At 203, according to the first relevance score and the second relevancescore, the method generates a relevance parameter score of each firstsearch result.

The difference between this step and the current technologies is thegeneration of the relevance parameter score based on the Score 1 and theScore 2 calculated at 202. In one embodiment, the detailed method ongeneration of the relevance parameter score of each first search resultmay be as follows: using a sum of the Score 1 and the Score 2 as therelevance parameter score of each first search result; or setting up aweighted value so that the relevance parameter score equals to a sum ofthe Score 1 and a product of the Score 2 multiplied by the weightedvalue. For example, assuming the weighted value is 2, the parametervalue for relevance=Score 1+2*Score 2. The present disclosure does notrestrict how the relevance parameter score of each first search resultis generated based on the Score 1 and the Score 2. Any variationsaccording to ideas of the present disclosure are within the protectionscope of the present disclosure. In this embodiment, the first searchresult set is not simply classified according to the Score 1, but isfurther processed by the new parameter generated by the Score 1 and theScore 2 parameters.

At 204, according to a preset number of one or more second searchresults and the relevance score, the method extracts the one or moresecond search results from the first search result set to display to theclient.

In this step, assuming the diversity field is preset as uid, theparameters required in this embodiment also include the present numberof second search results. The detailed preset number of second searchresults can be obtained by presetting the number of diversity values andthe number of recurring extractions, e.g., by calculating a product ofthe preset number of diversity values and the number of recurringextractions to obtain the number of second search results to beextracted. The number of diversity values is used to represent thenumber of first search results with different uids to be extracted inthe subsequent extracted second search results. For example, when thenumber of diversity values is 3, it indicates that 3 search results withdifferent uids are to be extracted. The number of recurring extractionsrepresents the number of second search results to present to the clientwhen the extracted second search results are subsequently displayed tothe client. Following the previous example, when the number of recurringextractions is 1, 3 second search results are returned; when the numberof recurring extractions is 2, 6 second search results are returned, andso on and so forth. Such extracted second search results include searchresults related to different uids.

FIG. 3 illustrates an exemplary method of a second embodiment inaccordance with the present disclosure. The method is described below.

At 301, according to query data submitted by a client, the methodobtains a first search result set relevant to the query data.

In practical applications, the present embodiment is applicable whensearch results of the search engine server have not achieved diversity.In other words, after the obtained first search results are rankedaccording to the first relevance score, search results with the sameattributes are still clustered together. For example, the top severalsearch results from the search engine server are all related a samesupplier. After 301, the first search result set is further processed ordetermined, such as whether the top several results of the first searchresult set belong to the same category. If the top several results ofthe first search result set belong to the same category, the subsequentsteps may be performed.

At 302, according to a preset diversity field, the method classifies thefirst search result set to obtain a respective subset corresponding toeach respective category of the first search result set.

In this embodiment, assuming the received preset diversity field is uid,as shown in the Table 1 below, the diversity field uid has three values{A, B, C}. In this embodiment, the first search result set {Doc}'ssub-sets relating to uid include {A1, A2, A3}, {B1, B2, B3}, and {C1,C2, C3}. The uid of A1˜A3 is A and A1˜A3 are search results for supplierA. The uid of B1˜B3 is B and B1˜B3 are search results for supplier B.The uid of C1˜C3 is C and C1˜C3 are search results for supplier C.

At 303, according to a first relevance score of each subset, the methodobtains a corresponding position of a first search result.

In this embodiment, the first search results in each subset are rankingaccording to the Score 1. As shown in the Table 1, Table 1 shows a firstsearch result set {Doc} and the corresponding uid and first relevancescore (Score 1) of each Doc.

TABLE 1 Search Result A1 A2 A3 B1 B2 B3 C1 C2 C3 Score 1 300 250 200 150100 50 40 30 20 uid A A A B B B C C C

At 304, according to a preset relationship between a second relevancescore and a position of each of the first search results in each subset,the method conducts a match to obtain the second reality score of eachof the first search results.

In practical applications, the relationship between the position of eachof the first search results in each subset and the Score 2 can berepresented by a preset function. For example, the second relevancescore of a respective first search result can be obtained by calculationof the preset retrieval function of the second relevance score. Theparameters of the retrieval functions are the position of each of thefirst search results after classification in each subset and the secondrelevance score. The relationship between the position of each of thefirst search results in each subset and the second relevance score canbe understood as the relationship between the position of a respectivesearch result in each subset after ranking according to the firstrelevance score and classification according to the diversity field andthe second relevance score. Such relationship can be represented by thefunction f(Position, Score 1). Such function can be adapted to any formand content depending upon the user's need or actual situation. Thepresent disclosure does not limit the detailed implementation of theform of the function. For example, in practice an example of thefunction is shown as follows:

float f ( int position, float score ) { if ( position == 1 ) return300.0f ; else return 0.0f ; }

The meaning of the above function is that when the ranking position ofthe first search result in the subset is 1, then 300 is returned or theScore 2 value is 300, and the Score 2 is 0 for the first search resultwith the other ranking positions.

At 305, according to the first relevance score and the second relevancescore, the method generates a relevance parameter score of each firstsearch result in the subset.

In one embodiment, a detailed method under the present disclosure forgeneration of the relevance parameter score of each first search resultmay include: using a sum of the second relevance score obtained at 304and the first relevance score of the first search result as therelevance parameter score of each first search result. Table 2 belowillustrates the first relevance score, the second relevance score, andthe relevance parameter score of each first search result in the subset.The present disclosure does not restrict how the relevance parameterscore is generated. Any simple variations according to ideas of thepresent disclosure are within the protection scope of the presentdisclosure.

TABLE 2 Search Result A1 A2 A3 B1 B2 B3 C1 C2 C3 Score1 300 250 200 150100 50 40 30 20 Score2 300 0 0 300 0 0 300 0 0 Score1 + 600 250 200 450100 50 340 30 20 Score2

At 306, according to the relevance parameter score, the method ranks thesubset after classification of the first search results.

Each subset after classification of the first search results is rankedaccording to the new parameter score obtained at 305. A new order ofeach search result in each subset is obtained after the new ranking. Inthis embodiment, after new ranking of the first search results, the topthree of each subset are A1, B1, and C1.

At 307, according to a ranking order, the method extracts a presetnumber of second search results from the ranked subset, and returns thesecond search results to the client.

The preset number of second search results can be obtained by presettingthe number of diversity values and the number of recurring extractions,e.g., by calculating a product of the preset number of diversity valuesand the number of recurring extractions to obtain the number of secondsearch results to be extracted.

The diversity field is used to present an attribute of the first searchresult. The diversity field value represents the value of the attributeof the first search result. In this embodiment, the diversity field isuid, the diversity values are A, B, and C. The first search results canbe classified into three subsets, e.g., A, B, and C, according to thediversity field. The number of second search results to be extracted canbe directly preset, or obtained by presetting the number of diversityvalues and the number of recurring extractions. The number of diversityvalues is used to represent the number of first search results withdifferent uids to be extracted in the subsequent extracted second searchresults. For example, when the number of diversity values is 3, itrepresents extracting 3 first search results for respective A, B, and Csuppliers. In this embodiment, the extraction of second search resultscan also be based on the number of recurring extractions. The number ofrecurring extractions represents the number of second search results tobe recurrently extracted for each category. For example, in thisembodiment, the number of recurring extractions (distinct_times) can beunderstood that when the number of recurring extractions is 1, then only3 are extracted from each supplier's search results as the second searchresults, and when the recurring extraction time is 2, 6 (=3*2) areextracted from each supplier's search results as the second searchresults. The extraction method in the case when the number ofextractions is 2 is the same as the method when the number ofextractions is 1, and so on.

If the second search results are extracted according to a setting thatdistinct_count=1 and distinct_times=1, the finally obtained secondsearch results are A1˜B1˜C1. If the second search results are extractedaccording to a setting that distinct_count=1 and distinct_times=3, thefinally obtained second search results are A1˜B1˜C1˜A2˜A3˜B2˜B3˜C2˜C3. Aperson of ordinary skill in the art can achieve different diversifiedeffects by setting different distinct_count, distinct_times, andf(Position, Score 1), thereby achieving a balance between thediversification of the search results and the relevance.

The method as illustrated in this embodiment shows that the top threerecords of the second search results include three search results theuid of which is A, B, and C, respectively. Thus the second searchresults finally returned to the client can achieve diversity and meetthe diversity requirements for search results. The diversificationprocess also implements optimization. Therefore there is lessconsumption of system resources, faster calculation, and moreflexibility in the method as illustrated in this embodiment.

FIG. 4 illustrates a third embodiment of a search method according tothe present disclosure. This embodiment can be understood as a detailedexample that applies the search method of the present disclosure. Themethod is described below.

At 401, according to a first relevance score, the method conducts asearch based on query data submitted by a client.

In this embodiment, after the search engine server obtains the firstsearch result, it conducts search of the current query data according tothe first relevance score.

At 402, according to a preset diversity field, the method extracts afirst search result set from the search results.

The diversity field needs to be preset. For example, in the embodiment2, the diversity field is preset as uid.

At 403, according to a preset diversity field value, the methodclassifies the first search result set to obtain a respective subsetcorresponding to each respective category of the first search resultset.

According to the selected uid in the first search result set, all searchresults related to suppliers A, B, and C are used as a subset relatingto uid of the first search results.

At 404, according to a first relevance score, the method obtains acorresponding position of a first search result in each subset.

At 405, according to a preset relationship between a second relevancescore and a position of each first search result after classification inthe respective subset, the method conducts a match to obtain the secondrelevance score of each first search result.

At 406, the method sums the first relevance score and the secondrelevance score to provide a relevance parameter score of each firstsearch result.

At 407, according to the relevance parameter score, the method ranks thesubsets after classification of the first search results.

At 408, according to a ranking order, the method extracts a presetnumber of second search results from the ranked subset.

The implementation process between the steps 404˜408 can refer todescriptions in the embodiment 2.

At 409, the method stores the query data, the second search results anda corresponding relationship between the query data and the secondsearch results into a database.

In this embodiment, after obtaining the user's current query data, thesecond search results, and the corresponding relationship between thequery data and the second search results, the method stores suchinformation in a database. A data table or any other permanent datastructure, for example, can be used as the form to store such data.

At 410, the method displays the second search results to the client.

At the meantime, the second search results are presented to client. Forexample, only the top three second search results in the embodiment 2may be displayed, e.g., A1, B2, and C2. Alternatively, all the searchresults in the subsets may be presented, such asA1˜B1˜C1˜A2˜A3˜B2˜B3˜C2˜C3.

In the interest of brevity, each of the aforementioned methods isdescribed as a combination of a series of actions. However, one ofordinary skill in the art would appreciate that the present disclosureis not limited by any particular order of the actions because, accordingto the present disclosure, some steps can be performed in other ordersor occur concurrently. In addition, one of ordinary skill in art wouldalso appreciate that the embodiments in the present disclosure arepreferred embodiments and some related steps or modules are notnecessarily required by the present disclosure.

Corresponding to the method as disclosed in the first embodiment of thepresent disclosure, by reference to FIG. 5, the present disclosure alsoprovides a first embodiment of a search system. The system may include:a retrieval unit 501, a calculation unit 502, a configuration unit 503,and an extraction unit 504.

The retrieval unit 501 is configured to, according to query datasubmitted by a client, obtain a first search result set relevant to thequery data.

In the search engine related technology field, a user's query is usuallyrepresented as symbol Query, and a result matching the Query isrepresented as Doc, and then a result set matching the Query is a Docset represented as {Doc}.

The calculation unit 502 is configured to, according to a firstrelevance score and a preset diversity field of each first search resultin the first search result set, calculates a second relevance score ofeach first search result. The preset diversity field represents anattribute category of a respective first search result.

After calculation of the Score 1 of each first search result in thefirst search result set, a second relative score (Score 2) needs to becalculated based on the preset diversity field and the Score 1. Thepreset diversity field represents the attribute category of therespective first search result, such as a uid (an identification ofsupplier) of each search result or geographical location information.The Score 2 is used to represent a score based on the Score 1 andranking of each first search result under the diversity field.

The configuration unit 503 is configured to, according to the firstrelevance score and the second relevance score, generate a relevanceparameter score of each first search result.

The detailed method to generate the relevance parameter score of eachfirst search result may include: using a sum of the Score 1 and theScore 2 as the relevance parameter score of each first search result.

The extraction unit 504 is configured to, according to a preset numberof one or more second search results and the relevance score, extractthe one or more second search results from the first search result setto display to the client.

Here, assuming the diversity field is preset as uid, the parametersrequired in this embodiment may also include the preset number of secondsearch results. The detailed preset number of second search results canbe obtained by presetting the number of diversity values and the numberof recurring extractions, e.g., by calculating a product of the presetnumber of diversity values and the number of recurring extractions toobtain the number of second search results to be extracted. The numberof diversity values is used to represent the number of first searchresults with different uids to be extracted in the subsequent extractedsecond search results. For example, when the number of diversity valuesis 3, it represents 3 search results with different uids are to beextracted.

The system as described in the present embodiment can be integrated intoa search engine server, or be an independent entity connected with asearch engine server. It is noted that when a method or system disclosedin the present disclosure are implemented by software, it can be anadditional function of the search engine server or have its owncorresponding coding. The present disclosure does not limit the form ofimplementation of the disclosed methods or systems.

Corresponding to the method as disclosed in the second embodiment of thepresent disclosure, by reference to FIG. 6, the present disclosure alsoprovides a second preferred embodiment of a search apparatus. Theapparatus may include: a retrieval unit 501, a first retrieval sub-unit601, a second retrieval sub-unit 602, a matching sub-unit 603, aconfiguration unit 503, a ranking sub-unit 604, and a first extractionsub-unit 605.

The retrieval unit 501 is configured to, according to query datasubmitted by a client, obtain a first search result set relevant to thequery data.

The first retrieval sub-unit 601 is configured to, according to a presetdiversity field, classify the first search result set to obtain arespective subset corresponding to each respective category of the firstsearch result set.

The second retrieval sub-unit 602 is configured to, according to a firstrelevance score in each subset, obtain a corresponding position of arespective first search result.

The matching unit 602 is configured to, according to a presetrelationship between a second relevance score and a position of each ofthe first search results in each subset, conduct a match to obtain thesecond reality score of each of the first search results.

The configuration unit 503 is configured to, according to the firstrelevance score and the second relevance score, generate a relevanceparameter score of each first search result.

A detailed method to generate the relevance parameter score of eachfirst search result may include: summing the first relevance score andthe second relevance score to provide the relevance parameter score ofeach first search result.

The ranking sub-unit 604 is configured to, according to the relevanceparameter score, rank each subset after classification of the firstsearch results.

The first extraction sub-unit 605 is configured to, according to aranking order, extract a preset number of second search results from theranked subsets, and to return the second search results to the client.

Corresponding to the method as disclosed in the third embodiment of thepresent disclosure, by reference to FIG. 7, the present disclosure alsoprovides a corresponding embodiment of a search system. The system mayinclude: a search sub-unit 701, a second extraction sub-unit 702, afirst retrieval sub-unit 601, a second retrieval sub-unit 602, amatching sub-unit 603, a configuration unit 503, a ranking sub-unit 604,a first extraction sub-unit 605, a store unit 703, and a display unit704.

The search sub-unit 701 is configured to, according to a first relevancescore, search query data submitted by a client.

The second extraction sub-unit 702 is configured to, according to apreset diversity field, extract first search results from searchresults.

The first retrieval sub-unit 601 is configured to, according to a presetdiversity field value, classify the first search result set to obtain arespective subset corresponding to each respective category of the firstsearch result set.

The second retrieval sub-unit 602 is configured to, according to a firstrelevance score of each subset, obtain a corresponding position of afirst search result.

The matching sub-unit 603 is configured to, according to a presetrelationship between a second relevance score and a position of eachfirst search result after classification in the respective subset,conduct a match to obtain the second relevance score of each firstsearch result.

The configuration unit 503 is configured to, according to the firstrelevance score and the second relevance score, generate a relevanceparameter score of each first search result.

A detailed method to generate the relevance parameter score of eachfirst search result may include: summing the first relevance score andthe second relevance score to provide the relevance parameter score ofeach first search result.

The ranking sub-unit 604 is configured to, according to the relevanceparameter score, rank each subset after classification of the firstsearch results.

The first extraction sub-unit 605 is configured to, according to aranking order, extract a preset number of second search results from theranked subsets, and return the second search results to the client.

The storing unit 703 is configured to store the query data, the secondsearch results and a corresponding relationship between query data andthe second search results into a database.

The display unit 704 is configured to display the second search resultsto the client.

The various exemplary embodiments are progressively described in thepresent disclosure. Same or similar portions of the exemplaryembodiments can be mutually referenced. Each exemplary embodiment has adifferent focus than other exemplary embodiments. For example, theexemplary apparatus embodiment has been described in a relatively simplemanner because of its fundamental correspondence with the exemplarymethod. Details thereof can be referred to corresponding portions of theexemplary method.

Finally, it is noted that any relational terms such as “first” and“second” in this document are only meant to distinguish one entity fromanother entity or one operation from another operation, but notnecessarily request or imply existence of any real-world relationship orordering between these entities or operations. Moreover, it is intendedthat terms such as “include”, “have” or any other variants meannon-exclusively “comprising”. Therefore, processes, methods, articles ordevices which individually include a collection of features may not belimited to those features, but may also include other features that arenot listed, or any inherent features of these processes, methods,articles or devices. Without any further limitation, a feature definedwithin the phrase “include a . . . ” does not exclude the possibilitythat process, method, article or device that recites the feature mayhave other equivalent features.

The search methods and systems provided in the present disclosure havebeen described in details above. The above exemplary embodiments areemployed to illustrate the concept and implementation of the presentdisclosure. The exemplary embodiments are provided to facilitateunderstanding of the techniques and respective core concepts of thepresent disclosure. Based on the concepts of this disclosure, one ofordinary skill in the art may make modifications to the practicalimplementation and application scopes. In conclusion, the content of thepresent disclosure shall not be interpreted as limitations of thisdisclosure.

1. A search method comprising: according to query data submitted by aclient, obtaining a first search result set of first search resultsrelevant to the query data; according to a first relevance score and apreset diversity field of each first search result in the first searchresult set, calculating a second relevance score of each first searchresult, the preset diversity field representing an attribute category ofa respective first search result; according to the first relevance scoreand the second relevance score, generating a relevance parameter scorefor each first search result; and according to a preset number of secondsearch results and the relevance parameter score, extracting the presentnumber of second search results from the first search result set todisplay to the client.
 2. The method as recited in claim 1, whereincalculating the second relevance score of each first search resultcomprises: according to the preset diversity field of each first searchresult in the first search result set, classifying the first searchresult set to obtain a respective subset corresponding to eachrespective attribute category of the first search result set; accordingto the first relevance score in each subset, obtaining a correspondingranking position of a respective first search result; and according to apreset relationship between the ranking position of the respective firstsearch result and the second relevance score, obtaining the secondrelevance score of each first search result.
 3. The method as recited inclaim 2, wherein extracting the preset number of second search resultsfrom the first search result set to display to the client comprises:according to the relevance parameter score, ranking each subset afterclassification of the first search results; and according to a rankingorder, extracting the preset number of second search resultsrespectively from the ranked subsets, the preset number of second searchresults being a product of a number of diversity values and a number ofrecurring extractions.
 4. The method as recited in claim 1, furthercomprising: storing the query data, the preset number of second searchresults, and a corresponding relationship between the query data and thepreset number of second search results into a database.
 5. The method asrecited in claim 1, wherein obtaining the first search result set offirst search results relevant to the query data comprises: according tothe first relevance score, conducting a search based on the query datasubmitted by the client; and according to the preset diversity field,extracting the first search results from search results of the search.6. The method as recited in claim 1, further comprising: displaying thepreset number of second search results to the client.
 7. The method asrecited in claim 1, wherein generating the relevance parameter score ofeach first search result comprises: summing the first relevance scoreand the second relevance score to provide the relevance parameter scorefor each first search result.
 8. A search system comprising: a retrievalunit that, according to query data submitted by a client, obtains afirst search result set of first search results relevant to the querydata; a calculation unit that, according to a first relevance score anda preset diversity field of each first search result in the first searchresult set, calculates a second relevance score of each first searchresult, the preset diversity field representing an attribute category ofa respective first search result; a configuration unit that, accordingto the first relevance score and the second relevance score, generates arelevance parameter score of each first search result; and an extractionunit that, according to a preset number of second search results and therelevance parameter score, extracts the present number of second searchresults from the first search result set to display to the client. 9.The system as recited in claim 8, wherein the calculation unitcomprises: a first retrieval sub-unit that, according to the presetdiversity field, classifies the first search result set to obtain arespective subset corresponding to each respective attribute category ofthe first search result set; a second retrieval sub-unit that, accordingto the first relevance score in each subset, obtains a correspondingranking position of a respective first search result; and a matchingunit that, according to a preset relationship between the rankingposition of each first search result and the second relevance score,obtains the second relevance score of the respective first searchresult.
 10. The system as recited in claim 9, wherein the extractionunit comprises: a ranking sub-unit that, according to the relevanceparameter score, ranks each first search result; and a first extractionsub-unit that, according to a ranking order, extracts the preset numberof second search results from the ranked subsets, the preset number ofsecond search results being a product of a number of diversity valuesand a number of recurring extractions.
 11. The system as recited inclaim 8, further comprising: a store unit that stores the query data,the preset number of second search results, and a correspondingrelationship between the query data and the preset number of secondsearch results into a database.
 12. The system as recited in claim 8,wherein the retrieval unit comprises: a searching sub-unit that,according to the first relevance score, conducts a search based on thequery data submitted by the client; and a second extraction sub-unitthat, according to the preset diversity field, extracts first searchresults from search results of the search.
 13. The system as recited inclaim 8, further comprising: a display unit that displays the presetnumber of second search results to the client.
 14. The system as recitedin claim 8, wherein the configuration unit sums the first relevancescore and the second relevance score to provide the relevance parameterscore of each first search result.